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medical-imaging-review

Write comprehensive literature reviews for medical imaging AI research. Use when writing survey papers, systematic reviews, or literature analyses on topics like segmentation, detection, classification in CT, MRI, X-ray, ultrasound, or pathology imaging. Triggers on requests for "review paper", "survey", "literature review", "综述", "systematic review", or mentions of writing academic reviews on deep learning for medical imaging.

Star
946
Category
Science
License
MIT
Last commit
Jul 20, 2026

skills/02-科学写作与学术交流/medical-imaging-review/SKILL.md

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Medical Imaging AI Literature Review Skill

Write comprehensive literature reviews following a systematic 7-phase workflow.

Quick Start

  1. Initialize project with three core files:

    • CLAUDE.md - Writing guidelines and terminology
    • IMPLEMENTATION_PLAN.md - Staged execution plan
    • manuscript_draft.md - Main manuscript

  2. Follow the 7-phase workflow (see references/WORKFLOW.md)

  3. Use domain-specific templates (see references/DOMAINS.md)

Core Principles

Writing Style

  • Hedging language: "may", "suggests", "appears to", "has shown promising results"
  • Avoid absolutes: Never say "X is the best method"
  • Citation support: Every claim needs reference
  • Limitations: Each method section needs a Limitations paragraph

Required Elements

  • Key Points box (3-5 bullets) after title
  • Comparison table for each major section
  • Performance metrics: Dice (0.XXX), HD95 (X.XX mm)
  • Figure placeholders with detailed captions
  • References: 80-120 typical, organized by topic

Paragraph Structure

Topic sentence (main claim)
  → Supporting evidence (citations + data)
  → Analysis (critical evaluation)
  → Transition to next paragraph

Literature Sources

Use multi-source strategy for comprehensive coverage:

SourceBest ForTools
ArXivLatest DL methods, preprintssearch_papers, read_paper
PubMedClinical validation, peer-reviewedpubmed_search_articles
ZoteroExisting library, organized refszotero_search_items

For MCP configuration details, see references/MCP_SETUP.md.

Standard Review Structure

# [Title]: State of the Art and Future Directions

## Key Points
- [3-5 bullets summarizing main findings]

## Abstract

## 1. Introduction
### 1.1 Clinical Background
### 1.2 Technical Challenges
### 1.3 Scope and Contributions

## 2. Datasets and Evaluation Metrics
### 2.1 Public Datasets (Table 1)
### 2.2 Evaluation Metrics

## 3. Deep Learning Methods
### 3.1 [Category 1]
### 3.2 [Category 2]
(Table 2: Method Comparison)

## 4. Downstream Applications

## 5. Commercial Products & Clinical Translation (Table 3)

## 6. Discussion
### 6.1 Current Limitations
### 6.2 Future Directions

## 7. Conclusion

## References

Method Description Template

### 3.X [Method Category]

[1-2 paragraph introduction with motivation]

**[Method Name]:** [Author] et al. [ref] proposed [method], which [innovation]:
- [Key component 1]
- [Key component 2]
Achieves Dice of X.XX on [dataset].

**Limitations:** Despite advantages, [category] methods face:
(1) [limit 1]; (2) [limit 2].

Citation Patterns

# Data citation
"...achieved Dice of 0.89 [23]"

# Method citation
"Gu et al. [45] proposed..."

# Multi-citation
"Several studies demonstrated... [12, 15, 23]"

# Comparative
"While [12] focused on..., [15] addressed..."

Reference Files

FilePurpose
references/WORKFLOW.mdDetailed 7-phase workflow
references/TEMPLATES.mdCLAUDE.md and IMPLEMENTATION_PLAN.md templates
references/DOMAINS.mdDomain-specific method categories
references/MCP_SETUP.mdMCP server configuration
references/QUALITY_CHECKLIST.mdPre-submission quality checklist

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